{"id":"W3122524391","doi":"","title":"EFFECT OF ARGENTINIAN PROGRAM FOR UNEMPLOYED HEADS OF HOUSEHOLDS ON CHILDREN’S SCHOOLING GAP","year":2011,"lang":"en","type":"article","venue":"International Business Research","topic":"Poverty, Education, and Child Welfare","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Beneficiary; Demographic economics; Sample (material); Socioeconomics; Economics; Gender gap; Demography; Business; Labour economics; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008686309,0.0001922149,0.0002858034,0.0004156178,0.0005775897,0.0004112006,0.0004098125,0.0004316399,0.00481936],"category_scores_gemma":[0.003771617,0.00008894868,0.0002647059,0.0003876633,0.0003582462,0.0002580861,0.001064576,0.0005165477,0.0002289721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001127445,"about_ca_system_score_gemma":0.001715306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03429574,"about_ca_topic_score_gemma":0.04810281,"domain_scores_codex":[0.9993752,0.0002447424,0.0000150874,0.00004263931,0.00006968789,0.0002526185],"domain_scores_gemma":[0.9982145,0.0004148016,0.0005602025,0.00006744665,0.0001694416,0.0005736016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003940632,0.002326847,0.8131114,0.0004781763,0.0002125052,0.0008173613,0.00229514,0.001404072,0.002220686,0.003361507,0.007358711,0.1624731],"study_design_scores_gemma":[0.00006701235,0.0004063094,0.9940509,0.00007225751,0.00005806381,0.00006380632,0.00117209,0.0002220816,0.0001850284,0.00009562774,0.003601692,0.000005114678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952713,0.0006720166,0.0000687746,0.0008705295,0.00002046331,0.00002002516,0.0002641642,0.0000149846,0.002797847],"genre_scores_gemma":[0.9971705,0.0004857408,0.0001195198,0.0001334595,0.00002879051,0.00003242816,0.0002340796,0.000004809011,0.001790643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03429574,"threshold_uncertainty_score":0.06819224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08793989271701519,"score_gpt":0.420565211465479,"score_spread":0.3326253187484638,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}